Human-algorithm interaction: Algorithmic pricing in hybrid laboratory markets - Hans-Theo Normann; Martin Sternberg (Heinrich Heine University Düsseldorf, Düsseldorf Institute for Competition Economics (DICE), 2022)
This paper investigates pricing in laboratory markets when human players interact with an algorithm. We compare the degree of competition when exclusively humans interact to the case of one firm delegating its decisions to an algorithm, an n-player generalization of tit-for-tat. We further vary whether participants know about the presence of the algorithm. When one of three firms in a market is an algorithm, we observe significantly higher prices compared to human-only markets. Firms employing an algorithm earn significantly less profit than their rivals. (Un)certainty about the actual presence of an algorithm does not significantly affect collusion, although humans do seem to perceive algorithms as more disruptive.
Keywords: C90; L41; 330; algorithms; collusion; human-computer interaction; labora-tory experiments